51 to 75 of 189 Model Validation Jobs in London

optimized for large-scale distributed systems using a high-performance grid computing platform Leverage Python, SQL, and Snowflake to analyze, construct, and validate model inputs Document methodologies to support internal and external model validation and compliance processes What you should have M.S. or PhD in mathematics, physical ...

teams deploy, monitor, retrain and govern models reliably at scale-from the ground up. Key Responsibilities ML Infrastructure & Deployment (40%): Build automated pipelines for model training, validation and deployment, plus model registries, feature stores and inference services, with self-serve tooling for Data Science teams. Model … workloads-covering latency, data quality and drift-and own rollback, rollout and incident response. MLOps Governance & Best Practice (20%): Establish controls for model lineage, reproducibility and audit trails, and introduce ML-specific CI/CD, testing and release automation. Collaboration & Enablement (10%): Partner with Data Science, Data Engineering ...

Ensure test coverage addresses CCR exposure calculations, netting, collateral and margining workflows, trade lifecycle events and relevant SA-CCR/IMM requirements. Oversee data validation and reconciliation testing across source feeds, risk engines and downstream outputs, investigating discrepancies with developers, business analysts and risk specialists. Maintain clear traceability between … timelines, requirements and proposed solutions where quality, testability or control standards may be compromised. Maintain testing documentation and evidence for internal audit, regulatory reviews, model validation teams and senior risk committees. Work with project managers, vendors, risk owners and technology leadership to resolve delivery issues and maintain consistent ...

enabled models, integrate diverse scientific data, and collaborate with multidisciplinary teams to drive discovery and decision-making. You will mentor junior colleagues, ensure robust model validation and governance, and contribute to a cutting-edge AI strategy across a global research network in an international environment. #J-18808-Ljbffr ...

predictive and prescriptive modelling solutions.Data ValidationThis role is responsible for ensuring that the data being used is accurate, reliable, and suitable for the model being built. This includes tasks such as data cleaning, data verification, data transformation and validation methods using both statistical and machine learning methods.Model UsageThis … role assists with marrying business understanding and knowledge with existing, appropriate, predictive and prescriptive model offerings (machine learning and AI) for commercial and/or operational benefits, given a known business challenge.Model DeploymentThe Junior Data Scientist assists in the integration and implementation of relevant models into the applicable business ...

delivered on time, within budget and to a high quality. The role is accountable for driving the adoption of best practice across modelling, experimentation, validation and implementation, ensuring insights translate into practical and measurable business outcomes. The Data Science Manager will provide technical leadership across advanced analytics, machine learning … with strong SQL knowledge and experience using machine learning frameworks Experience with cloud platforms (Azure, AWS or GCP), data visualisation tools and MLOps/model deployment practices Understanding of data governance, responsible AI and Generative AI/LLM technologies; relevant professional qualification desirable At BDO, we’ll help ...

ready insights grounded in trusted data and established metrics. About the role: We are seeking a Data Scientist III to help the design and validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning … including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality). Analyse large-scale IP datasets to extract insights and improve model performance. Establish best practices for model evaluation, validation, and benchmarking. Translate experimental results into clear product recommendations and business impact. Collaborate with ...

Science teams deploy, monitor, retrain and govern models reliably at scale—from the ground up.Key Responsibilities ML Infrastructure & Deployment (40%): Build automated pipelines for model training, validation and deployment, plus model registries, feature stores and inference services, with self-serve tooling for Data Science teams.Model Monitoring & Operations … recovery for ML workloads—covering latency, data quality and drift—and own rollback, rollout and incident response.MLOps Governance & Best Practice (20%): Establish controls for model lineage, reproducibility and audit trails, and introduce ML-specific CI/CD, testing and release automation.Collaboration & Enablement (10%): Partner with Data Science, Data Engineering ...

degree in a technical field and Python experience are required, with familiarity in AI/ML concepts and Agile methods. You will contribute to model validation, testing, and delivering small to medium AI features in collaboration with MLOps and #J-18808-Ljbffr ...

production, working with engineering to deploy on GCP. Investigate new data sources and methods to close gaps in maritime domain awareness. Communicate findings and model behavior clearly to both technical and non-technical stakeholders, including customers. Collaborate closely with the wider Theia data science and engineering teams on shared ...

language for the large-scale analysis and production of securities data Research and development of market dynamics across multiple asset classes Prototyping, testing, and validation of our client's proprietary models supporting and coaching more junior team members Requirements Proven financial markets experience, ideally within an investment bank ...

that private equity-backed businesses use to run their value creation plans. As Vice President, Data Solutions, you’ll own the architecture, data operating model and client relationship. You’ll work out what the business needs and why, shape the design, define how data is owned, governed and managed ...

data engineers, technical project managers, marketing operations, and account leadership. Advanced expertise in data architecture for campaign execution, including complex data models, audience selection, validation, identity resolution, QA, and data-driven trigger logic. Relevant platform certifications or accreditations are strongly preferred (e.g., Adobe Certified Master/Expert ...

across platforms such as Relativity, Epiq AI, Reveal AI, and other advanced review or analytics platforms.* Develop and refine prompts, instructions, classification criteria, and model guidance for generative AI and LLM-enabled tools, with a focus on consistency, quality, defensibility, and practical review outcomes.* Advise clients and internal teams … appropriate use cases, limitations, risks, defensibility considerations, and quality control measures for AI-enabled review workflows.* Explain statistical concepts, validation methodologies, sampling approaches, model performance, and review metrics to audiences with varying levels of technical, legal, and operational knowledge.* Demonstrate a strong understanding of the full eDiscovery lifecycle ...

cross-asset workflows. What's the role? We are looking for a senior product manager to run IPQA's analytics architecture and drive model delivery at scale, ensuring our analytics continue to lead as client and market needs evolve. You will work at the intersection of quantitative finance, engineering … clients across Terminal, Enterprise Data and Enterprise Products. At the core of this role is a founding conviction: analytics at scale require a model-agnostic design, where the architecture enforces consistency and transparency across models, asset classes and client workflows. You will work closely with our quant and engineering ...

platforms Develop and apply data quality frameworks to assess and ensure fitness-for-purpose of diverse data sources for specific analytical questions Implement strong model evaluation practices including cross-validation strategies, calibration assessment, and transparent reporting of model performance and limitations Build scalable, automated processes for delivering … health data and wearable/sensor-derived data types Experience with cloud-based scalable compute and deployment patterns for large-scale data processing and model training #LI-Hybrid We hire for skills and capabilities, not just credentials. How We Work Where you work matters – because collaboration, innovation and patient ...

Support clients in navigating emerging AI regulations, standards, and guidance while enabling innovation and business value. Facilitate workshops, governance forums, risk assessments, and operating model design activities with senior stakeholders. Live in-person whiteboarding sessions to problem solve as a team, alongside asynchronous communication on Teams. Hybrid working with … client site. You must be an established consulting professional with experience delivering projects focused on AI governance, responsible AI, AI risk management, model governance, or emerging technology regulation within the private sector. Ideally, you should have experience consulting with Life Sciences, Government or Consumer & Manufacturing sector clients. Even ...

anomaly detection, variance analysis, drift detection, forecasting, behavioural signals, and prediction, ensuring they are accurate, explainable, resilient, and regulator-ready. Own the full model lifecycle from problem framing, data exploration, feature engineering, back-testing, validation, deployment, monitoring, tuning, and incident response when models degrade or fail in production. … models within financial services or other highly regulated, high‐availability environments. Deep expertise in applied data science and ML, including statistical modelling, predictive analytics, model development, validation, deployment, monitoring, and optimisation across the full model lifecycle. Strong hands‐on technical skills, with the ability to work directly ...

Strong hands-on experience with ESRI ArcGIS Enterprise, ArcGIS Pro, Portal for ArcGIS and/or ArcGIS Online. Experience in GIS data management, modelling, validation, transformation and quality assurance. Practical experience using FME (Safe Software) or equivalent ETL tools. Good knowledge of spatial data formats, GIS databases, coordinate systems ...

entering a pivotal phase of growth and technological advancement. Its solutions are already being embedded into generative AI pipelines, delivering measurable improvements in model performance, while also addressing the rising energy demands of large-scale AI adoption. With a focus on practical deployment and a clear roadmap to fault ...

encourage applications from people with diverse and underrepresented backgrounds and perspectives. Why you? Design and implement AI/ML-driven solutions throughout the entire model development life cycle. Research and develop state‐of‐the‐art machine learning models and agentic systems to solve a variety of scientific tasks. Deliver ...

people with diverse and underrepresented backgrounds and perspectives. In this role you will Design and implement AI/ML-driven solutions throughout the entire model development life cycle. Research and develop state‐of‐the‐art machine learning models and agentic systems to solve a variety of scientific tasks. Deliver ...

companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability. We work with customers across 28 countries from 10 VOIS locations: Albania … Italy, Greece, and Portugal. About this role We are seeking a Lead Data Scientist to provide senior scientific leadership for Data Science and applied-model development within Digital Engineering, Digital & IT. Based flexibly in Newbury or Paddington, UK, you will translate customer, commercial and operational challenges into testable analytical ...

affect the deal, and write clear, practical fixes. What you will bring At least five years building, evaluating or assuring machine learning or language model systems. Hands on experience of fine tuning open source language models and designing evaluation suites. Working knowledge of ISO/IEC 42001, the NIST … Risk Management Framework or the EU AI Act. The ability to explain model risk in plain words to founders, buyers and lawyers. Experience with health, clinical or other regulated data is a strong plus. Experience of due diligence, audit or model validation work is a strong plus. ...

heterogeneity of operating room environments. With customers all over the world operating rooms are often different which creates unique opportunities for problem solving and model design. Own the full model lifecycle including but not limited to data curation, model implementation, training, validation, deployment, and maintenance. Development … within Proximie environment to enable dynamic model training and performance evaluation while integrating with Proximie’s data lakes. Document solutions and contribute to internal knowledge sharing and capability building. Requirements PhD in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered ...